Overview

Dataset statistics

Number of variables14
Number of observations246
Missing cells6
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory28.0 KiB
Average record size in memory116.5 B

Variable types

Text4
Categorical4
DateTime2
Numeric4

Dataset

Description원주시에 위치한 아파트의 분양조건(임대,분양) 정보(건물명,주소,전화번호,세대수, 면적 등) 아파트에 관련된 여러 정보들
Author강원도 원주시
URLhttps://www.data.go.kr/data/3043750/fileData.do

Alerts

관리기관 has constant value ""Constant
관리기관전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
동수 is highly overall correlated with 세대수 and 2 other fieldsHigh correlation
세대수 is highly overall correlated with 동수 and 2 other fieldsHigh correlation
대지면적(제곱미터) is highly overall correlated with 동수 and 2 other fieldsHigh correlation
연면적(제곱미터) is highly overall correlated with 동수 and 2 other fieldsHigh correlation
분양조건 is highly imbalanced (67.1%)Imbalance
관리사무소전화번호 has 5 (2.0%) missing valuesMissing
아파트명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:42:27.439116
Analysis finished2023-12-12 08:42:30.423467
Duration2.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

아파트명
Text

UNIQUE 

Distinct246
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T17:42:30.660288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.7317073
Min length4

Characters and Unicode

Total characters2148
Distinct characters231
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique246 ?
Unique (%)100.0%

Sample

1st row해동아파트
2nd row선아아파트
3rd row동주아파트
4th row치악맨션아파트
5th row단계아파트
ValueCountFrequency (%)
아파트 5
 
1.7%
원주 5
 
1.7%
2차 4
 
1.4%
롯데캐슬 4
 
1.4%
사랑으로부영아파트 2
 
0.7%
더퍼스트 2
 
0.7%
봉화산 2
 
0.7%
내안애카운티 2
 
0.7%
에듀파크 2
 
0.7%
호반베르디움 2
 
0.7%
Other values (263) 265
89.8%
2023-12-12T17:42:31.192058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
파 222
 
10.3%
아 220
 
10.2%
트 217
 
10.1%
차 85
 
4.0%
49
 
2.3%
주 46
 
2.1%
단 45
 
2.1%
원 44
 
2.0%
지 41
 
1.9%
1 40
 
1.9%
Other values (221) 1139
53.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1929
89.8%
Decimal Number 127
 
5.9%
Space Separator 49
 
2.3%
Open Punctuation 12
 
0.6%
Close Punctuation 12
 
0.6%
Uppercase Letter 12
 
0.6%
Lowercase Letter 3
 
0.1%
Dash Punctuation 2
 
0.1%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
파 222
 
11.5%
아 220
 
11.4%
트 217
 
11.2%
차 85
 
4.4%
주 46
 
2.4%
단 45
 
2.3%
원 44
 
2.3%
지 41
 
2.1%
동 29
 
1.5%
이 27
 
1.4%
Other values (197) 953
49.4%
Decimal Number
ValueCountFrequency (%)
1 40
31.5%
2 37
29.1%
3 18
14.2%
4 9
 
7.1%
5 7
 
5.5%
6 6
 
4.7%
8 4
 
3.1%
7 3
 
2.4%
9 2
 
1.6%
0 1
 
0.8%
Uppercase Letter
ValueCountFrequency (%)
L 3
25.0%
H 3
25.0%
C 2
16.7%
O 1
 
8.3%
B 1
 
8.3%
Q 1
 
8.3%
K 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 3
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1929
89.8%
Common 204
 
9.5%
Latin 15
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
파 222
 
11.5%
아 220
 
11.4%
트 217
 
11.2%
차 85
 
4.4%
주 46
 
2.4%
단 45
 
2.3%
원 44
 
2.3%
지 41
 
2.1%
동 29
 
1.5%
이 27
 
1.4%
Other values (197) 953
49.4%
Common
ValueCountFrequency (%)
49
24.0%
1 40
19.6%
2 37
18.1%
3 18
 
8.8%
( 12
 
5.9%
) 12
 
5.9%
4 9
 
4.4%
5 7
 
3.4%
6 6
 
2.9%
8 4
 
2.0%
Other values (6) 10
 
4.9%
Latin
ValueCountFrequency (%)
e 3
20.0%
L 3
20.0%
H 3
20.0%
C 2
13.3%
O 1
 
6.7%
B 1
 
6.7%
Q 1
 
6.7%
K 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1929
89.8%
ASCII 219
 
10.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
파 222
 
11.5%
아 220
 
11.4%
트 217
 
11.2%
차 85
 
4.4%
주 46
 
2.4%
단 45
 
2.3%
원 44
 
2.3%
지 41
 
2.1%
동 29
 
1.5%
이 27
 
1.4%
Other values (197) 953
49.4%
ASCII
ValueCountFrequency (%)
49
22.4%
1 40
18.3%
2 37
16.9%
3 18
 
8.2%
( 12
 
5.5%
) 12
 
5.5%
4 9
 
4.1%
5 7
 
3.2%
6 6
 
2.7%
8 4
 
1.8%
Other values (14) 25
11.4%

주소
Text

Distinct245
Distinct (%)99.6%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T17:42:31.630414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20
Mean length16.455285
Min length13

Characters and Unicode

Total characters4048
Distinct characters119
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique244 ?
Unique (%)99.2%

Sample

1st row강원도 원주시 남부시장길 2
2nd row강원도 원주시 치악로 1650
3rd row강원도 원주시 치악로 1652
4th row강원도 원주시 치악로 1803
5th row강원도 원주시 서원대로 205
ValueCountFrequency (%)
원주시 247
23.3%
강원도 246
23.2%
문막읍 19
 
1.8%
남원로 18
 
1.7%
지정면 12
 
1.1%
무실로 12
 
1.1%
시청로 12
 
1.1%
치악로 12
 
1.1%
가곡리 11
 
1.0%
원문로 10
 
0.9%
Other values (276) 462
43.5%
2023-12-12T17:42:32.217400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
815
20.1%
원 535
13.2%
시 262
 
6.5%
강 248
 
6.1%
주 247
 
6.1%
도 246
 
6.1%
1 164
 
4.1%
로 158
 
3.9%
2 97
 
2.4%
4 85
 
2.1%
Other values (109) 1191
29.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2462
60.8%
Space Separator 815
 
20.1%
Decimal Number 762
 
18.8%
Dash Punctuation 9
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 535
21.7%
시 262
10.6%
강 248
10.1%
주 247
10.0%
도 246
10.0%
로 158
 
6.4%
길 82
 
3.3%
문 30
 
1.2%
번 30
 
1.2%
동 28
 
1.1%
Other values (97) 596
24.2%
Decimal Number
ValueCountFrequency (%)
1 164
21.5%
2 97
12.7%
4 85
11.2%
5 79
10.4%
3 73
9.6%
6 63
 
8.3%
0 63
 
8.3%
8 56
 
7.3%
7 45
 
5.9%
9 37
 
4.9%
Space Separator
ValueCountFrequency (%)
815
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2462
60.8%
Common 1586
39.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 535
21.7%
시 262
10.6%
강 248
10.1%
주 247
10.0%
도 246
10.0%
로 158
 
6.4%
길 82
 
3.3%
문 30
 
1.2%
번 30
 
1.2%
동 28
 
1.1%
Other values (97) 596
24.2%
Common
ValueCountFrequency (%)
815
51.4%
1 164
 
10.3%
2 97
 
6.1%
4 85
 
5.4%
5 79
 
5.0%
3 73
 
4.6%
6 63
 
4.0%
0 63
 
4.0%
8 56
 
3.5%
7 45
 
2.8%
Other values (2) 46
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2462
60.8%
ASCII 1586
39.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
815
51.4%
1 164
 
10.3%
2 97
 
6.1%
4 85
 
5.4%
5 79
 
5.0%
3 73
 
4.6%
6 63
 
4.0%
0 63
 
4.0%
8 56
 
3.5%
7 45
 
2.8%
Other values (2) 46
 
2.9%
Hangul
ValueCountFrequency (%)
원 535
21.7%
시 262
10.6%
강 248
10.1%
주 247
10.0%
도 246
10.0%
로 158
 
6.4%
길 82
 
3.3%
문 30
 
1.2%
번 30
 
1.2%
동 28
 
1.1%
Other values (97) 596
24.2%

분양조건
Categorical

IMBALANCE 

Distinct10
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
분양
205 
사원임대
 
10
국민임대
 
10
민간임대
 
8
임대
 
6
Other values (5)
 
7

Length

Max length9
Median length2
Mean length2.3658537
Min length2

Unique

Unique4 ?
Unique (%)1.6%

Sample

1st row분양
2nd row분양
3rd row분양
4th row분양
5th row분양

Common Values

ValueCountFrequency (%)
분양 205
83.3%
사원임대 10
 
4.1%
국민임대 10
 
4.1%
민간임대 8
 
3.3%
임대 6
 
2.4%
분양(분양전환) 3
 
1.2%
영구임대 1
 
0.4%
임대(민영10년) 1
 
0.4%
공공임대 1
 
0.4%
국민,영구임대 1
 
0.4%

Length

2023-12-12T17:42:32.392442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:42:32.549974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분양 205
83.3%
사원임대 10
 
4.1%
국민임대 10
 
4.1%
민간임대 8
 
3.3%
임대 6
 
2.4%
분양(분양전환 3
 
1.2%
영구임대 1
 
0.4%
임대(민영10년 1
 
0.4%
공공임대 1
 
0.4%
국민,영구임대 1
 
0.4%

관리사무소전화번호
Text

MISSING 

Distinct238
Distinct (%)98.8%
Missing5
Missing (%)2.0%
Memory size2.1 KiB
2023-12-12T17:42:32.884820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.008299
Min length12

Characters and Unicode

Total characters2894
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique235 ?
Unique (%)97.5%

Sample

1st row033-764-6485
2nd row033-762-5043
3rd row033-763-7262
4th row033-764-8190
5th row033-744-9740
ValueCountFrequency (%)
033-734-5011 2
 
0.8%
033-742-0181 2
 
0.8%
033-735-2601 2
 
0.8%
033-763-3443 1
 
0.4%
033-731-6635 1
 
0.4%
033-742-0878 1
 
0.4%
033-743-3658 1
 
0.4%
033-744-5200 1
 
0.4%
033-764-6485 1
 
0.4%
033-731-7137 1
 
0.4%
Other values (228) 228
94.6%
2023-12-12T17:42:33.410986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 683
23.6%
- 482
16.7%
0 375
13.0%
7 345
11.9%
4 232
 
8.0%
6 182
 
6.3%
5 153
 
5.3%
2 142
 
4.9%
1 124
 
4.3%
8 92
 
3.2%
Other values (2) 84
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2411
83.3%
Dash Punctuation 482
 
16.7%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 683
28.3%
0 375
15.6%
7 345
14.3%
4 232
 
9.6%
6 182
 
7.5%
5 153
 
6.3%
2 142
 
5.9%
1 124
 
5.1%
8 92
 
3.8%
9 83
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 482
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2894
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 683
23.6%
- 482
16.7%
0 375
13.0%
7 345
11.9%
4 232
 
8.0%
6 182
 
6.3%
5 153
 
5.3%
2 142
 
4.9%
1 124
 
4.3%
8 92
 
3.2%
Other values (2) 84
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2894
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 683
23.6%
- 482
16.7%
0 375
13.0%
7 345
11.9%
4 232
 
8.0%
6 182
 
6.3%
5 153
 
5.3%
2 142
 
4.9%
1 124
 
4.3%
8 92
 
3.2%
Other values (2) 84
 
2.9%

사업승인일
Date

Distinct207
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1979-04-28 00:00:00
Maximum2019-02-25 00:00:00
2023-12-12T17:42:33.619472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:33.845034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사용검사일
Date

Distinct232
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
Minimum1979-12-07 00:00:00
Maximum2022-05-31 00:00:00
2023-12-12T17:42:34.019052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:34.230145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

동수
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8943089
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:42:34.415809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median5
Q38
95-th percentile12.75
Maximum26
Range25
Interquartile range (IQR)5

Descriptive statistics

Standard deviation3.9316881
Coefficient of variation (CV)0.66703123
Kurtosis2.9577908
Mean5.8943089
Median Absolute Deviation (MAD)2.5
Skewness1.3275655
Sum1450
Variance15.458172
MonotonicityNot monotonic
2023-12-12T17:42:34.553304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
4 34
13.8%
2 30
12.2%
5 25
10.2%
6 23
9.3%
1 22
8.9%
3 21
8.5%
7 20
8.1%
8 19
7.7%
10 14
5.7%
11 10
 
4.1%
Other values (8) 28
11.4%
ValueCountFrequency (%)
1 22
8.9%
2 30
12.2%
3 21
8.5%
4 34
13.8%
5 25
10.2%
6 23
9.3%
7 20
8.1%
8 19
7.7%
9 10
 
4.1%
10 14
5.7%
ValueCountFrequency (%)
26 1
 
0.4%
19 2
 
0.8%
17 2
 
0.8%
16 2
 
0.8%
15 3
 
1.2%
13 3
 
1.2%
12 5
 
2.0%
11 10
4.1%
10 14
5.7%
9 10
4.1%

세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct208
Distinct (%)84.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean457.3374
Minimum20
Maximum1538
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:42:34.716266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile88.25
Q1239.25
median410
Q3625.5
95-th percentile935.75
Maximum1538
Range1518
Interquartile range (IQR)386.25

Descriptive statistics

Standard deviation279.33714
Coefficient of variation (CV)0.61079006
Kurtosis0.90189872
Mean457.3374
Median Absolute Deviation (MAD)185
Skewness0.8780239
Sum112505
Variance78029.237
MonotonicityNot monotonic
2023-12-12T17:42:34.908458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
110 3
 
1.2%
499 3
 
1.2%
45 3
 
1.2%
200 3
 
1.2%
616 2
 
0.8%
240 2
 
0.8%
291 2
 
0.8%
334 2
 
0.8%
192 2
 
0.8%
299 2
 
0.8%
Other values (198) 222
90.2%
ValueCountFrequency (%)
20 1
 
0.4%
30 1
 
0.4%
36 1
 
0.4%
45 3
1.2%
50 2
0.8%
60 1
 
0.4%
76 1
 
0.4%
80 1
 
0.4%
87 1
 
0.4%
88 1
 
0.4%
ValueCountFrequency (%)
1538 1
0.4%
1430 1
0.4%
1335 1
0.4%
1243 1
0.4%
1133 1
0.4%
1124 1
0.4%
1116 1
0.4%
1110 1
0.4%
996 1
0.4%
990 1
0.4%

대지면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct241
Distinct (%)98.4%
Missing1
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean21942.556
Minimum1302
Maximum83399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:42:35.429421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1302
5-th percentile3123
Q19440
median18313.6
Q330918.1
95-th percentile50692.8
Maximum83399
Range82097
Interquartile range (IQR)21478.1

Descriptive statistics

Standard deviation16109.736
Coefficient of variation (CV)0.73417773
Kurtosis1.4839399
Mean21942.556
Median Absolute Deviation (MAD)9882.6
Skewness1.1905633
Sum5375926.3
Variance2.595236 × 108
MonotonicityNot monotonic
2023-12-12T17:42:35.640733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40660.9 3
 
1.2%
6029.0 2
 
0.8%
11835.0 2
 
0.8%
1910.0 1
 
0.4%
16376.2 1
 
0.4%
40097.88 1
 
0.4%
18424.69 1
 
0.4%
30918.1 1
 
0.4%
13895.1 1
 
0.4%
27178.0 1
 
0.4%
Other values (231) 231
93.9%
ValueCountFrequency (%)
1302.0 1
0.4%
1491.0 1
0.4%
1611.0 1
0.4%
1694.0 1
0.4%
1910.0 1
0.4%
2168.0 1
0.4%
2201.0 1
0.4%
2343.0 1
0.4%
2390.224 1
0.4%
2479.0 1
0.4%
ValueCountFrequency (%)
83399.0 1
0.4%
78254.9 1
0.4%
76685.0 1
0.4%
70885.0 1
0.4%
68896.7 1
0.4%
67449.0 1
0.4%
64009.0 1
0.4%
62685.0 1
0.4%
60633.0 1
0.4%
56235.0 1
0.4%

연면적(제곱미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct243
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean53339.877
Minimum1570
Maximum240881.41
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.3 KiB
2023-12-12T17:42:35.830428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1570
5-th percentile6184.575
Q121496.25
median43086.655
Q374758.398
95-th percentile128758.5
Maximum240881.41
Range239311.41
Interquartile range (IQR)53262.148

Descriptive statistics

Standard deviation41088.849
Coefficient of variation (CV)0.7703214
Kurtosis1.6291529
Mean53339.877
Median Absolute Deviation (MAD)24818.755
Skewness1.1982602
Sum13121610
Variance1.6882935 × 109
MonotonicityNot monotonic
2023-12-12T17:42:35.992245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
105768.0 3
 
1.2%
30356.0 2
 
0.8%
3094.0 1
 
0.4%
59412.912 1
 
0.4%
54180.64 1
 
0.4%
75254.158 1
 
0.4%
111309.58 1
 
0.4%
72430.47 1
 
0.4%
113213.557 1
 
0.4%
45439.934 1
 
0.4%
Other values (233) 233
94.7%
ValueCountFrequency (%)
1570.0 1
0.4%
1676.0 1
0.4%
1836.0 1
0.4%
2647.0 1
0.4%
2784.0 1
0.4%
2809.0 1
0.4%
2975.0 1
0.4%
3094.0 1
0.4%
3921.0 1
0.4%
5010.0 1
0.4%
ValueCountFrequency (%)
240881.409 1
0.4%
204681.0 1
0.4%
167249.0 1
0.4%
151874.0 1
0.4%
150306.84 1
0.4%
145737.506 1
0.4%
143963.8408 1
0.4%
143848.9 1
0.4%
136841.0 1
0.4%
135826.1853 1
0.4%

층수
Text

Distinct87
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2023-12-12T17:42:36.247391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length3.800813
Min length1

Characters and Unicode

Total characters935
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)20.7%

Sample

1st row5
2nd row5
3rd row5
4th row7
5th row5
ValueCountFrequency (%)
15 66
26.8%
5 32
 
13.0%
20 9
 
3.7%
18 6
 
2.4%
12 5
 
2.0%
10 4
 
1.6%
6 4
 
1.6%
15(-1 4
 
1.6%
13 4
 
1.6%
11~15(-2 4
 
1.6%
Other values (77) 108
43.9%
2023-12-12T17:42:36.787081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 255
27.3%
5 147
15.7%
2 106
11.3%
~ 79
 
8.4%
- 65
 
7.0%
( 61
 
6.5%
) 61
 
6.5%
0 51
 
5.5%
3 32
 
3.4%
8 22
 
2.4%
Other values (4) 56
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 669
71.6%
Math Symbol 79
 
8.4%
Dash Punctuation 65
 
7.0%
Open Punctuation 61
 
6.5%
Close Punctuation 61
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 255
38.1%
5 147
22.0%
2 106
15.8%
0 51
 
7.6%
3 32
 
4.8%
8 22
 
3.3%
9 20
 
3.0%
4 18
 
2.7%
6 13
 
1.9%
7 5
 
0.7%
Math Symbol
ValueCountFrequency (%)
~ 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 935
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 255
27.3%
5 147
15.7%
2 106
11.3%
~ 79
 
8.4%
- 65
 
7.0%
( 61
 
6.5%
) 61
 
6.5%
0 51
 
5.5%
3 32
 
3.4%
8 22
 
2.4%
Other values (4) 56
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 935
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 255
27.3%
5 147
15.7%
2 106
11.3%
~ 79
 
8.4%
- 65
 
7.0%
( 61
 
6.5%
) 61
 
6.5%
0 51
 
5.5%
3 32
 
3.4%
8 22
 
2.4%
Other values (4) 56
 
6.0%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
강원도 원주시청
246 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도 원주시청
2nd row강원도 원주시청
3rd row강원도 원주시청
4th row강원도 원주시청
5th row강원도 원주시청

Common Values

ValueCountFrequency (%)
강원도 원주시청 246
100.0%

Length

2023-12-12T17:42:36.955956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:42:37.059777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
강원도 246
50.0%
원주시청 246
50.0%

관리기관전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
033-737-3445
246 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row033-737-3445
2nd row033-737-3445
3rd row033-737-3445
4th row033-737-3445
5th row033-737-3445

Common Values

ValueCountFrequency (%)
033-737-3445 246
100.0%

Length

2023-12-12T17:42:37.171682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:42:37.272484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
033-737-3445 246
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size2.1 KiB
2022-08-23
246 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-23
2nd row2022-08-23
3rd row2022-08-23
4th row2022-08-23
5th row2022-08-23

Common Values

ValueCountFrequency (%)
2022-08-23 246
100.0%

Length

2023-12-12T17:42:37.372138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:42:37.470281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-23 246
100.0%

Interactions

2023-12-12T17:42:29.480938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.051599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.495793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.001765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.609612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.157275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.612514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.088014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.713085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.285015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.751995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.226253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.815574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.379574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:28.888428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:42:29.365870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:42:37.549710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분양조건동수세대수대지면적(제곱미터)연면적(제곱미터)층수
분양조건1.0000.0000.5900.5110.0000.542
동수0.0001.0000.7570.7440.8710.755
세대수0.5900.7571.0000.8710.8230.787
대지면적(제곱미터)0.5110.7440.8711.0000.7900.866
연면적(제곱미터)0.0000.8710.8230.7901.0000.884
층수0.5420.7550.7870.8660.8841.000
2023-12-12T17:42:37.677636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
동수세대수대지면적(제곱미터)연면적(제곱미터)분양조건
동수1.0000.8010.8420.7540.000
세대수0.8011.0000.8650.8490.216
대지면적(제곱미터)0.8420.8651.0000.8470.178
연면적(제곱미터)0.7540.8490.8471.0000.031
분양조건0.0000.2160.1780.0311.000

Missing values

2023-12-12T17:42:29.954862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:42:30.204902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-12-12T17:42:30.362996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

아파트명주소분양조건관리사무소전화번호사업승인일사용검사일동수세대수대지면적(제곱미터)연면적(제곱미터)층수관리기관관리기관전화번호데이터기준일자
0해동아파트강원도 원주시 남부시장길 2분양033-764-64851979-08-021979-12-072361910.03094.05강원도 원주시청033-737-34452022-08-23
1선아아파트강원도 원주시 치악로 1650분양033-762-50431979-06-071980-03-0551104547.08355.05강원도 원주시청033-737-34452022-08-23
2동주아파트강원도 원주시 치악로 1652분양033-763-72621979-08-071980-05-2561566210.09798.05강원도 원주시청033-737-34452022-08-23
3치악맨션아파트강원도 원주시 치악로 1803분양033-764-81901979-04-281983-01-2411856297.54913950.07강원도 원주시청033-737-34452022-08-23
4단계아파트강원도 원주시 서원대로 205분양033-744-97401983-12-311984-11-282681070885.042834.05강원도 원주시청033-737-34452022-08-23
5세경1차아파트강원도 원주시 남원로 661분양033-763-88571984-09-261985-08-24832013287.019150.05강원도 원주시청033-737-34452022-08-23
6자유아파트강원도 원주시 중앙시장길 11분양033-743-62391986-05-191987-09-112919365.068686.310강원도 원주시청033-737-34452022-08-23
7원동1차아파트강원도 원주시 무실로 121분양033-765-74121986-11-291987-11-251243025900.020690.05강원도 원주시청033-737-34452022-08-23
8세경2차아파트강원도 원주시 강변로 353분양033-762-81411987-06-181988-06-2452008951.012117.05강원도 원주시청033-737-34452022-08-23
9정암아파트강원도 원주시 흥양로 98분양033-745-81841987-12-281988-10-17528011835.016147.05강원도 원주시청033-737-34452022-08-23
아파트명주소분양조건관리사무소전화번호사업승인일사용검사일동수세대수대지면적(제곱미터)연면적(제곱미터)층수관리기관관리기관전화번호데이터기준일자
236내안애카운티 에듀파크 2단지강원도 원주시 단구동 1711분양033-764-27472017-12-192020-06-03534816101.052944.019~20강원도 원주시청033-737-34452022-08-23
237이지더원 2차 더 그레이스강원도 원주시 지정면 가곡리1468분양033-743-83382017-09-042020-06-24777639882.0106388.019~29강원도 원주시청033-737-34452022-08-23
238봉화산 벨라시티3차 아파트강원도 원주시 단계동 1221분양033-732-65552018-04-272020-11-12549921277.068659.023~29강원도 원주시청033-737-34452022-08-23
239원주 LH천년나무 6단지강원도 원주시 태장동 산145-48임대033-731-19892018-03-292020-12-0744642479.028607.012~15강원도 원주시청033-737-34452022-08-23
240스타클래스 엔에이치에프강원도 원주시 흥업면 흥업리 1838임대033-765-20212018-12-312021-09-28628716860.039433.011~25강원도 원주시청033-737-34452022-08-23
241더샵원주센트럴파크1단지강원도 원주시 무실동 1921분양033-764-53002018-06-292021-11-04993634371.0124758.028강원도 원주시청033-737-34452022-08-23
242더샵원주센트럴파크2단지강원도 원주시 명륜동 856분양033-763-34432018-06-292021-11-291083842494.0128181.028강원도 원주시청033-737-34452022-08-23
243골드클래스아파트강원도 원주시 행구동 1863임대033-747-88902019-02-252022-04-11740219799.069387.015강원도 원주시청033-737-34452022-08-23
244더샵원주센트럴파크3단지강원도 원주시 명륜동 857분양033-762-9700~12018-07-202022-05-311068724878.096566.020강원도 원주시청033-737-34452022-08-23
245더샵원주센트럴파크4단지강원도 원주시 무실동 1922분양033-737-05672018-07-232022-04-2941959236.036717.020강원도 원주시청033-737-34452022-08-23